Redux - Making Impossible States Impossible - javascript

TL;DR
Is there a library which makes something like Elm-Union Types possible in JavaScript with Redux and ImmutableJS?
Idea
Hi!
I am rather new to Redux, still exploring best patterns to use. I spent some time learning Elm and in Elm the core focus of whole application is the Model.
The core prinicple of Elm is making errorless applications. In comparison with JavaScript, Elm is packed with basic types (String, List, Boolean...) as it's also a static typed language. On the other hand you can use ImmutableJS and Flow and get pretty decent amount of full types and type check also in JavaScript, which makes this very even.
But the contrast between Elm and JavaScript comes with a feature called Union Types. With Union Types you can say something like:
type alias User = {
name: String
}
type Session = LoggedOut | LoggedIn User
What this means is that we have two options when it comes to session:
There is no session and we have no information about the user.
User is authenticated and we know who the user is.
This is extremely useful when dealing with "HOC" as we can say simply:
case session of
LoggedOut ->
displayLoginButton
LoggedIn user ->
displayUser user
Furthermore you can use the same pattern when fetching data. When data is fetching the state is Fetching once it is fetched, the state is Fetched Data and in case of an error, the state is FetchingError Error.
This makes data very secure and very clean. The same problem written in JavaScript/Redux would normaly be tackled something like this:
const model = {
loading: false,
loaded: false,
error: null,
data: null
}
At first this might seem normal, but as you think you see that "impossible" situations can be encountered. For example:
const model = {
loading: true,
loaded: true,
error: null,
data: null
}
The data can't be loading and be loaded at the same time!
Question
Is there a way to acheive similar concept with JavaScript-Redux and still remain the immutability of ImmutableJS?
Or if there's a way to rearrange the model to make impossible states impossible in Redux?
P.S.
Great talk about this in Elm: "Making Impossible States Impossible" by Richard Feldman

No, there's nothing specifically built into React or Redux that enables that. That sort of thing is really more at the language level. You might want to look into TypeScript or Flow to add static types that help with that. Beyond that, you can probably put something together using an explicit state machine approach or careful reducer logic checks.
My React/Redux links list has a section on static typing tools that may be useful in getting started. In addition, since you mentioned the "loading states" example, the React and Ajax category in my list specifically links to several articles that discuss ways to handle that concept in TS, Flow, and a couple other solutions.

You can hack it like this:
const Session = {
LOGGED_IN: user => ({ type: 'LOGGED_IN', user }),
LOGGED_OUT: () => ({ type: 'LOGGED_OUT' })
}
switch (session.type) {
case 'LOGGED_IN': {
viewUser(session.user)
}
case 'LOGGED_OUT': {
viewLoginButton()
}
}

Related

React redux shared object between components

I'm coming from Angular over to React and therefore are scratching my head, trying to figure out how to share an object between two components.
I'm running into trouble when I update my object, as the new values aren't updated across components. As I'm not allowed to reference the same object (due to immutability in Redux) I'm having a hard time to figure out how to do this the best.
What's the correct, most simple and best way of achieving what I want? Here's an illustration:
(this illustration does not represent my app but has been simplified to make it easier to understand what I want to achieve. My React components are nested in multiple layers, which is why I thought Redux would be the solution)
... and here's how I've structured my redux object so far:
export default function reducer(state = {
blocks: [{ title: '', description: '' }],
currentBlock: null,
}, action) {
switch (action.type) {
case 'UPDATE_BLOCK_TITLE':
return {...state,
blocks: state.blocks.map((block, i) => block === action.payload.block ? {...block, title: action.payload.title} : block)
}
case 'SET_CURRENT_BLOCK':
return {...state, currentBlock: action.payload }
}
return state;
}
My UPDATE_BLOCK_TITLE case makes sure to update a field in the object, whilst my SET_CURRENT_BLOCK updates which block to be shown on the right-hand side.
I find it a little cumbersome if I have to update both the title and the currentBlock every time I change the title, especially coming from Angular where this sort of thing would be very easy to achieve.
Maybe I'm looking at implementing it the wrong way? Please let me know what the best way of achieving this is.
The Redux way is to keep your data normalized.
According to your use-case, you should keep only the block.id (or any other block identifier) in currentBlock. Doing it that way - when you modify the blocks store itself, all related components will receive the updated block, because they will rely on the relation block.id.
How do I organize nested or duplicate data in my state?
Data with IDs, nesting, or relationships should generally be stored in a “normalized” fashion: each object should be stored once, keyed by ID, and other objects that reference it should only store the ID rather than a copy of the entire object. It may help to think of parts of your store as a database, with individual “tables” per item type. Libraries such as normalizr and redux-orm can provide help and abstractions in managing normalized data.
I would suggest you to walk through the official Redux documentation about Structuring Reducers. It's very well written and structured, so you will learn the main concepts and best practices from Redux creators.

Redux: Is it wrong, this all-around action creator pattern?

I'm a newbie. I'm not sure, is using below the pattern wrong/silly?
import { createAction, handleActions } from "redux-actions";
const CHANGE_STATE = "appState/CHANGE_STATE";
export const changeState = createAction(CHANGE_STATE, (key, val) => ({ [key]: val }));
const initialState = {
maxBodySize: 1920,
isMaxBody: true,
isMobile: false
};
export default handleActions(
{
[CHANGE_STATE]: (state, { payload: changedState }) => {
const newState = {
...state,
...changedState
};
return newState;
}
},
initialState
);
Only one actionCreator editable every state. Like this:
// Can editable every state with 'changeState' action.
appState.changeState("isMaxBody", true);
appState.changeState("isMobile", true);
appState.changeState("maxBodySize", 960);
Can I continue to use this handy pattern?
If this pattern is bad, give some instructions to me, please.
Can I continue to use this handy pattern
I don't see why you "couldn't". It seems perfectly valid, in a strict sense.
As for whether or not it's a good idea, well, that's open to opinion, but I would not recommend using this pattern. Here's a few reasons:
You lose the abstraction between "actions" and "state modification". It's nice to be able to say "perform this action", and not have to worry about what the actual state changes are. Some actions may modify multiple parts of state. All of that is abstracted away from you, making it more controlled and testable. In a similar vein, this probably won't work well with, say, middleware, for similar reasons.
Modifying string properties "looks icky", and generally seems error prone. You'll get no help from tooling if you accidentally put a typo in a property name somewhere in your app.
Similar to the above, you lose any ability to leverage static typing (flow or TypeScript, for instance). Having written a decently large React/Redux app in a team, I highly recommend using something like TypeScript, and this pattern will not work well in a strongly/statically typed app.
Those are my opinions, derived from my experience. If the pattern works well for you and what you are trying to accomplish, you might find that it's just fine.
P.S. if you are going to use a pattern like this, I don't see why you wouldn't just do e.g. appState.changeState({isMaxBody: true}); instead of appState.changeState("isMaxBody", true);. It seems a little cleaner, and at least closer to allowing better typing.

Redux/Java: Managing normlized data & multiple model representations per entity

We are building a new app using React/Redux which is rendered server side.
We wish to follow best practice for Redux and normalize our data on the server before it's passed into the initial state for the store.
For this example, let's say we have a generic 'Products' entity that can be quite complex and is normalized on the root of our store and page level state in another object on the root of the store. So the structure and Reducers follow the typical 'slice reducer' pattern and will look like this:
{
page_x_state: PageReducer
products: ProductsReducer
}
We are using combine reducers to merge the reducers before passing them into the store.
Theoretical use case: We have a 'products' page that shows a list of basic product info. A user can click on a product to show a modal which then loads and shows the complete product data.
For the above example, the state sent from the server will contain only basic product models (3 or 4 fields), this is enough to render the table and fetching all product information at this point is wasteful and not very performant.
When a user clicks a product we will do an AJAX call fetch all data for that product. Once we have all data for the single product, should we update the instance in the products store with a full model? If so, we would then end up with a set of objects all of which could be different states (some could have minimal fields vs some which are full-blown objects with 10s of fields). Is this the best way to handle it?
Also, I would be interested to hear any thoughts of managing different representations of the same underlying model on the server and how to map it to the Redux store (in Java ideally).
EDIT:
Explicitly answering your first question, if your reducers are built up correctly your whole state tree should initialize with absolutely no data in it. But should be the correct shape. Your reducers should always have a default return value - when rendering server side - Redux should only render the initial state
After server-side rendering, when the store (that is now client side) needs updating because of a user action, your state shape for all of your product data is already there (it's just that some of it will probably be default values.). Rather than overwriting an object, your just filling in the blanks so to speak.
Lets say, in your second level view you need name, photo_url, price and brand and the initial view has 4 products on it, your rendered store would look something like this:
{
products: {
by_id: {
"1": {
id: "1",
name: "Cool Product",
tags: [],
brand: "Nike",
price: 1.99,
photo_url: "http://url.com",
category: "",
product_state: 0,
is_fetching: 0,
etc: ""
},
"2": {
id: "2",
name: "Another Cool Product",
tags: [],
brand: "Adidas",
price: 3.99,
photo_url: "http://url2.com",
category: "",
product_state: 0,
is_fetching: 0,
etc: ""
},
"3": {
id: "3",
name: "Crappy Product",
tags: [],
brand: "Badidas",
price: 0.99,
photo_url: "http://urlbad.com",
category: "",
product_state: 0,
is_fetching: 0,
etc: ""
},
"4": {
id: "4",
name: "Expensive product",
tags: [],
brand: "Rolex",
price: 199.99,
photo_url: "http://url4.com",
category: "",
product_state: 0,
is_fetching: 0,
etc: ""
}
},
all_ids: ["1", "2", "3", "4"]
}
}
You can see in the above data some keys are just empty strings or an empty array. But we have our data we need for the actual initial rendering of the page.
We could then make asynchronous calls on the client in the background immediately after the server has rendered and the document is ready, the chances are the server will return those initial calls before the user tries to get the data anyway. We can then load subsequent products on user request. I don't think that's the best approach but it's the one that makes most sense to me. Some other people might have some other ideas. It entirely depends on your app and use-case.
I would only keep one products object in state though and keep ALL the data pertaining to products in there.
I recently deployed an app into production and i'll share some of my
insights. The app, whilst not being too large in size, had a complex
data structure and having gone through the whole process as a newbie
to Redux in production (and having guidance from my architect) – These
are some of our takeaways. There's no right way in terms of architecture but there certainly are some things to avoid or do.
1. Before firing into writing your reducers design a 'static' state
If you don't know where you are going, you can't get there. Writing the whole structure of your state out flat will help you reason about how your state will change over time. We found this saved us time because we didn't have to really rewrite large sections.
2. Designing you state
keep it simple. The whole point of Redux is to simplify state management. We used a lot of the tips from the egghead.io tutorials on Redux that were created by Dan Abramov. They are clear really helped solve a lot of issues we were encountering. i'm sure you've read the docs about normalising state but the simple examples they gave actually carried through in most data patterns we implemented.
Rather than creating complex webs of data each chunk of data only held it's own data if it needed to reference another piece of it data it only referenced it by id we found this simple pattern covered most of our needs.
{
products: {
by_id: {
"1": {
id: "1",
name: "Cool Product",
tags: ["tag1", "tag2"],
product_state: 0,
is_fetching: 0,
etc: "etc"
}
},
all_ids: ["1"]
}
}
In the example above, tags might be another chunk of data with a similiar data structure using by_id and all_ids. All over the docs and tut, Abramov keeps referencing relational data and relational databases this was actually key for us. At first we kept looking at the UI and designing our state around how we thought we were going to show it. When this clicked and we started grouping the data based on it's relationship to other pieces of data, things started to click into place.
Quickly flipping to your question, I would avoid duplicating any data, as mentioned in another comment, personally i'd simply create a key in the state object called product_modal. let the modal take care of it's own state...
{
products: {
...
},
product_modal: {
current_product_id: "1",
is_fetching: true,
is_open: true
}
}
We found following this pattern with page state worked really well as well...we just treated it like any other piece of data with an id/name etc.
3. Reducer Logic
make sure reducers keep track of their own state. a lot of our reducers looked quite similiar, at first this felt like DRY hell but then we quickly realised the power of more reducers...say an action is dispatched and you want to update a whole chunk of state..no probs just check in your reducer for the action and return the new state. If you only want to update one or two fields in the same state...then you just do the same thing but only in the fields you want changing. most of our reducers were just simply a switch statement with an occasional nested if statement.
Combining Reducers
We didnt use combineReducers, we wrote our own. It wasn't hard, it helped us understand what was going on in Redux, and it allowed us to get a little smarter with our state. This tut was invaluable
Actions
Middleware is your friend...we used fetch API with redux-thunk to make RESTful requests. We split the required data requests into separate actions which called store.dispatch() for each data chunk that needed updating for the call. Each dispatch dispatched another action to update state. This kept our state updated modularly and allowed us to update large sections, or granularly as needed.
Dealing with an API
Ok so there's way too much to deal with here. I'm not saying our way is the best...but it has worked for us. Cut short...we have an internal API in java with publically exposed endpoints. The calls from this API didn't always map to the front end easily. We haven't implemented this, but ideally, an initial init endpoint could have been written on their end to get a lump of initial data that was needed to get things rolling on the front end for speeds sake.
We created a public API on the same server as the app, written in PHP. This API abstracted the internal API's endpoints (and in some cases the data too) away from the front end and the browser.
When the app would make a GET request to /api/projects/all the PHP API would then call our internal API, get the necessary data (sometimes across a couple of requests) and return that data in a usable format that redux could consume.
This might not be the ideal approach for a javascript app but we didn't have the option to create a new internal API structure, we needed to use one that has existed for several years, we have found the performance acceptable.
should we update the instance in the products store with a full model
It should be noted that Java and ReactJs+Redux don't have much conceptual overlap. Everything is a Javascript Object, not an Object with a Class.
Generally, storing all the data you receive in the Redux store state is the way to go. To work around the fact that some of the data will be minimal and some will be fully loaded you should make a conditional ajax call in the onComponentWillMount method of the individual product display container.
class MyGreatProduct extends React.Component {
onComponentWillMount() {
if(!this.props.thisProduct.prototype.hasProperty( 'somethingOnlyPresentInFullData' )) {
doAjaxCall(this.props.thisProduct.id).then((result) => {
this.props.storeNewResult(result.data);
}).catch(error=>{ ... })
}
}
// the rest of the component container code
}
const mapStateToProps = (state, ownProps) => {
return {
thisProduct: state.products.productInfo[ownProps.selectedId] || {id: ownProps.selectedId}
}
}
const mapDispatchToProps = (dispatch, ownProps) => {
return {
storeNewResult: (data) => { dispatch(productDataActions.fullProductData(data)) }
}
export default connect(mapStateToProps, mapDispatchToProps)(MyGreatProduct);
With this code, it should be somewhat clear how agnostic the components and containers can be regarding the exact data available in the Store at any given time.
Edit: In terms of managing different representations of the same underlying model on the server and how to map it to the Redux store, I'd try to use the same relative looseness you are dealing with once you have JSON. This should eliminate some coupling.
What I mean by this is just add the data you have to a JSObject to be consumed by React + Redux, without worrying too much about what values could potentially be stored in the Redux state during the execution of the application.
There's probably no right answer, just which strategy you prefer:
The simplest strategy is to add another piece to your reducer called selectedProduct and always overwrite it with the full object of the currently selected product. Your modal would always display the details of the selectedProduct. The downfalls of this strategy are that you aren't caching data in the case when a user selects the same product a second time, and your minimal fields aren't normalized.
Or you could update the instance in your Products store like you said, you'll just need logic to handle it. When you select a product, if it's fully loaded, render it. If not, make the ajax call, and show a spinner until its fully loaded.
If you don't have a concern with storing extra that data in the redux store it's not actually going to hit your performance very much if you use a normalized state. So on that front I would recommend caching as much as you can without risking security.
I think the best solution for you would be to use some redux middleware so your front end doesn't care how it gets the data. It will dispatch an action to the redux store and the middleware can determine whether or not it needs an AJAX call to get the new data. If it does need to fetch the data then the middleware can update the state when the AJAX resolves, if it doesn't then it can just discard the action because you already have the data. This way you can isolate the issue of having two different representations of the data to the middleware and implement a resolution there for it so your front end just asks for data and doesn't care how it gets it.
I don't know all the implementation details so as Jeff said its probably more what you prefer but I would definitely recommend adding some middleware to handle your AJAX calls if you haven't already it should make interfacing with the store much simpler.
If you want to read more on middleware the Redux documentation is pretty good.
https://redux.js.org/docs/advanced/Middleware.html
You could store each entity as an object of its various representations. In the action creator that updates the entity, include the representation as an argument:
const receiveProducts = (payload = [], representation = 'summary') => ({
type: 'PRODUCTS_RECEIVED',
payload, representation
});
const productReducer = (state = {}, action) => {
case 'PRODUCTS_RECEIVED': {
const { payload, representation } = action;
return {
...state,
...payload.reduce((next, entity) => {
next[entity.id] = {
...next[entity.id],
[representation]: entity
};
return next
}, {})
}
}
};
This means that whoever is calling receiveProducts() needs to know which representation is returned.

How to feed dependencies between Flux stores using Immutable.js?

I have a simple chat application going on and the following stores:
MessageStore - messages of all users/chat groups
ChatGroupStore - all chat groups
UserStore - all users in general
I'm using immutable.js to store data. The thing is, MessageStore needs to use data from ChatGroupStore and UserStore, each message is constructed like this:
{
id: 10,
body: 'message body',
peer: {...} // UserStore or ChatGroupStore item - destination
author: {...} // UserStore or ChatGroupStore item - creator of the message
}
How am I suppose to update MessageStore items according to ChatGroupStore and UserStore update?
I was using AppDispatcher.waitFor() like this:
MessageStore.dispatchToken = AppDispatcher.register(function(action) {
switch(action.actionType) {
case UserConstants.USER_UPDATE:
AppDispatcher.waitFor([
UserStore.dispatchToken
]);
// update message logic
break;
}
});
From my point of view I would have to wait for the UserStore to update and then find all the messages with the updated user and update them. But how do I find the updated peer? I think a search in UserStore by reference wouldn't be enough since immutable data doesn't keep the reference when data changes, then I would have to apply more on queries. But then I would have to apply query logic of other stores inside MessageStore handler.
Currently I'm storing peers as a reference inside each message, maybe should I change to just:
{
id: 10,
peer: {
peerType: 'user', // chatGroup
peerId: 20
}
}
Would be great if anybody could shed some light about it. I'm really confused.
The best option I can see as a solution in all occasions is not to keep related data nested and to avoid transformations on data that comes from server, this will reduce the amount of work I need to do to keep the data up to date at all times. Then in your view, all you have to do is to subscribe to changes and put together the necessary data.
Alternative to Flux
There's also a good and well maintained state container solution called Redux which I suggest everyone to at least try. It has only one store and combines the whole state into a single deep object, although you can create each reducer separately. It also has a good way to integrate it with React, see Usage with React.

Updating Data between two components in React

I am new to React and I don't know what's the best way to do this.
I have a list of cars and on clicking each row it should show slide to full page details of that car.
My code structure is:
I have App which renders two components. CarList and CarDetails. Car Details is hidden initially. The reason I rendered carDetails in app is because it's a massive fix template so I would like to render this once when app is loaded and only update it's data when each row clicked.
CarList also renders CarRow component which is fine.
Now my problem is I have a getDetails function on CarRow component which is making a call to get the details based on the car id. How to get carDetails component data updated ? I used
this.setState({itemDetails:data});
but seems state of the carRow is not the same reference as state in carDetails.
Any help?
This is a fundamental issue that lots of thought and man-hours has gone into in order to try and solve. It probably can't be answered, except on a surface level, in a StackOverflow post. It's not React-centric, either. This is an issue across most applications, regardless of the framework you're using.
Since you asked in the context of React, you might consider reading into flux, which is the de-facto implementation of this one-way data-flow idea in concert with React. However, that architecture is by no means "the best". There are simply advantages and disadvantages to it like everything else.
Some people don't like the idea of the global "event bus" that flux proposes. If that's the case, you can simply implement your own intermediate data layer API that collects query callbacks and A) invokes the callbacks on any calls to save data and B) refreshes any appropriate queries to the server. For now, though, I'd stick with flux as it will give you an idea of the general principles involved in having the things that most people consider to be "good", like a single source of truth for your data, one way flow, etc.
To give a concrete example of the callback idea:
// data layer
const listeners = [];
const data = {
save: save,
query: query
};
function save(someData) {
// save data to the server, and then...
.then(data => {
listeners.forEach(listener => listener(data));
});
}
function query(params, callback) {
// query the server with the params, then
listeners.push(callback);
}
// component
componentWillMount() {
data.query(params, data => this.setState({ myData: data }));
},
save() {
// when the save operation is complete, it will "refresh" the query above
data.save(someData);
}
This is a very distilled example and doesn't address optimization, such as potential for memory leaks when moving to different views and invoking "stale" callbacks, however it should give you a general idea of another approach.
The two approaches have the same policy (a single source of truth for data and one way data flow) but different implementations (global "event bus" which necessitates keeping track of events, or the simple callback method, which can necessitate a form of memory management).

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